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In this experimental study, we use a data-driven machine learning framework based on genetic programing (GP) to discover model-free control laws (individuals) for suppressing self-excited thermoacoustic oscillations in a prototypical laminar combustor. This GP framework relies on an evolutionary algorithm to make decisions based on natural selection. Starting from an initial generation of individuals, we rank their performance based on a cost function that accounts for the trade-off between the state cost (thermoacoustic amplitude) and the input cost (actuator power). We then breed subsequent generations of individuals via a tournament in which the direct forwarding of elite individuals occurs alongside genetic operations such as mutation, replication, and crossover. We implement this GP control framework in both closed-loop and open-loop forms, followed by benchmarking against conventional open-loop control based on time-periodic forcing. We find that while all three control strategies can achieve similarly large reductions in thermoacoustic amplitude, GP closed-loop control consumes the least actuator power, making it the most efficient. It achieves this efficiency by learning an actuation mechanism that exploits the strong heat-release-rate amplification of the open flame at its preferred mode, even though the GP algorithm has never seen the open flame itself. This study demonstrates the feasibility of using GP to discover new and more efficient model-free individuals for suppressing self-excited thermoacoustic oscillations, providing a promising approach to data-driven feedback control of combustion devices. [ABSTRACT FROM AUTHOR]

We numerically investigate the forced synchronization of the self-excited flow behind a plunging airfoil in ground effect at a Reynolds number of Re = 1000. On varying the plunging amplitude and frequency, we find a rich array of nonlinear dynamics, such as a period-1 limit cycle due to natural vortex shedding as well as two-frequency quasiperiodicity on a torus attractor ( T 2 ). For certain non-resonant plunging frequencies without a ground surface, we find that low-dimensional chaos emerges via the Ruelle–Takens–Newhouse route. However, we find that the chaos can be suppressed by introducing a ground surface, inducing a direct transition from T 2 quasiperiodicity to 1:1 phase locking as the plunging amplitude rises over the boundaries of the Arnold tongue. Apart from suppressing chaos, the ground surface also causes the lift and drag coefficients to become less sensitive to the plunging motion itself. Knowledge of the critical plunging conditions required for forced synchronization and chaos could be useful in various engineering applications, such as the design of pico air vehicles. [ABSTRACT FROM AUTHOR]

Understanding the thermal transport in polymer-bonded explosives (PBXs) is critical for enhancing the safety and reliability during PBX design, especially in the absence of effective experimental measurements. In this work, we rigorously investigated the phonon properties of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) and polyvinylidene fluoride (PVDF) and calculated the interfacial thermal conductance using an ab initio approach. The diffuse mismatch model and anharmonic inelastic model were adopted to examine the interfacial thermal conductance as a function of temperature for the TATB–PVDF interface. Our calculation results indicate that low-frequency phonon modes and the two-phonon process play dominant roles in the thermal transport at interfaces. In contrast, high-order phonon processes involving three to eight phonons accounted for around 8% of the interfacial thermal conductance at the TATB–PVDF interface. Phonon properties, such as the velocity and degree of phonon density overlap, are discussed for the TATB–PVDF and 1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane (HMX)–PVDF interfaces to estimate the interfacial thermal conductance of PBXs. This study provides a theoretical explanation for the establishment of a research method for PBX thermal transport. [ABSTRACT FROM AUTHOR]